融合体验 打造沉浸交互新范式 滴水OS 2.0 Pre秉持"以用户为中心"的设计理念，创新打造中控屏与全景视界联动的智能座舱显示形态，既保障行车安全，又兼顾信息展示的丰富度， 实现双重价值的精准平衡。其搭载的"智穹融合实境"HMI系统，将车道级地图(LD Map)、SR(Surrounding Reality)与AVM全景影像三大独立图层深度整合， 实现多维度数据的一屏集成，让信息呈现更直观、更高效；全场景3D渲染双屏联动功能全面覆盖实时驾驶、弹射模式、充电桌面、休息室等多元用车场 景，搭配超650万面高精度模型渲染与实时光影特效，以"一镜到底"的丝滑界面转场，为用户带来身临其境的沉浸式视觉享受。 图为中科创达联合创始人兼执行总裁耿增强正在发布滴水 OS 2.0 Pre Thunder Sott CES2026年1月7日，CES2026国际消费电子展现场，中科创达以"AI-Native Road-Ready"为主题，成功举办滴水OS 2.0 Pre全球发布会，正式推出全新一 代AI原生整车操作系统。该系统凭借"融合体验、AI原生、更快量产"三大核心优势，通过创新的智能座舱显示布局与智能交互设计，重新定义智能汽 ...

Core Viewpoint - The company, Zhongke Chuangda, is positioned as a leading global provider of intelligent operating systems, benefiting significantly from AI-driven industrial transformation through its unique "operating system + edge intelligence" strategy [1] Group 1: Business Segments - Intelligent Software: The business revenue for the intelligent software segment reached 841 million yuan in H1 2025, reflecting a year-on-year growth of 10.52% [2] - Intelligent Automotive: The intelligent automotive segment achieved revenue of 1.189 billion yuan in H1 2025, with a year-on-year increase of 7.85% [3] - Intelligent IoT: The intelligent IoT segment experienced a remarkable revenue growth of 136% year-on-year in H1 2025, driven by the rapid expansion of edge AI applications [3] Group 2: Market Trends and Projections - The global smartphone market is expected to see a moderate recovery, with a projected year-on-year growth of 1% in shipments by 2025, driven by the increasing penetration of AI features [1] - The global automotive generative AI market is anticipated to grow at a CAGR of 23.8% from 2025 to 2034, indicating a strong growth trajectory for the intelligent automotive sector [2] - The global edge AI market is forecasted to grow from 321.9 billion yuan in 2025 to 1.2 trillion yuan by 2029, with a CAGR of 39.6% [3] Group 3: Globalization and Strategic Initiatives - The company reported overseas revenue of 1.558 billion yuan in H1 2025, marking an impressive year-on-year growth of 81.41%, showcasing the effectiveness of its "globalization + localization" strategy [3] - The company is set to launch its AI-native vehicle operating system, Drip OS, in 2025, which supports a full-chip platform and large model access, indicating a strategic move to capture the growing demand for integrated automotive solutions [2] Group 4: Financial Projections - The company is expected to achieve revenues of 7.314 billion yuan, 9.415 billion yuan, and 11.436 billion yuan for the years 2025, 2026, and 2027, respectively, with year-on-year growth rates of 35.8%, 28.7%, and 21.5% [4] - The projected net profit attributable to the parent company is forecasted to be 578 million yuan, 746 million yuan, and 964 million yuan for the years 2025, 2026, and 2027, reflecting growth rates of 41.9%, 29.0%, and 29.3% [4]

Core Insights - The impact of AI on server operating systems is mutual, necessitating advancements in both AI applications and operating systems to support them effectively [2][3] Group 1: Market Trends and Predictions - The global AI server market is projected to exceed $120 billion by 2025, indicating a significant shift in the role of operating systems from passive tools to active power management centers [3] - The demand for heterogeneous computing is reshaping the foundational logic of server operating systems, requiring compatibility with various hardware types such as CPU, GPU, DPU, FPGA, and ASIC [3][4] Group 2: Technical Challenges - Server operating systems face several challenges, including the need for full architecture compatibility and dynamic resource scheduling to support AI model training [3][4] - Performance bottlenecks and cluster stability are critical issues, particularly with the training of trillion-parameter models that require terabyte-level memory and face cumulative failure rates in large clusters [3][4] Group 3: Evolution of Operating Systems - Operating systems are evolving from simple tools to intelligent agents capable of smart resource allocation and management [4][5] - Two main technical directions are emerging: one involves using large models to create operating system kernels, while the other focuses on upgrading existing kernels through intelligent adaptations [4][5] Group 4: Data Privacy and Security - AI applications in sensitive fields like healthcare and finance demand stringent data privacy and security measures, prompting operating systems to enhance their security frameworks [5][6] Group 5: Ecosystem Integration - The fragmentation of software and hardware ecosystems poses significant challenges for server operating systems, necessitating improved compatibility and optimization across diverse computing resources [5][6] - The establishment of alliances, such as the Longxi Intelligent Computing Infrastructure Alliance, aims to enhance compatibility and collaboration among AI chip manufacturers, server vendors, and operating system developers [9][10] Group 6: Future Directions - The future of server operating systems lies in their ability to integrate AI capabilities, transforming them into intelligent operational assistants that can preemptively address issues and enhance system stability [8][9] - The concept of AI-native operating systems is gaining traction, requiring a reconfiguration of existing systems to better support AI environments [6][7]